Visual and semiquantitative assessment of cranial artery inflammation with FDG-PET/CT in giant cell arteritis

Background and aim: Assessing cranial artery inflammation plays an important role in the diagnosis of cranial giant cell arteritis (C-GCA). However, current diagnostic tests are limited. The use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT imaging is an established tool for assessing large vessel inflammation but is currently not used for assessment of the cranial arteries. This study aimed to evaluate the accuracy of FDG-PET/CT in the diagnosis of biopsy proven C-GCA and its relation to clinical presentation. Methods: This retrospective case control study included temporal artery biopsy (TAB) positive C-GCA patients and ageand sex-matched controls. FDG-PET/CT scans were performed according to EANM/EARL guidelines, visually assessed by an experienced nuclear medicine physician, and semiquantitatively assessed using the maximum standardised uptake value (SUVmax). The visual and semiquantitative assessments were performed on the temporal arteries, maxillary arteries, vertebral arteries, and occipital arteries. Clinical signs and symptoms were scored for comparison. Results: A total of 24 C-GCA patients and 24 controls were included in the study. Visual analysis revealed an 83% sensitivity and a 75% specificity. Receiver operating characteristic (ROC) analysis of the semiquantitative assessment revealed a 79% sensitivity and a 92% specificity when measuring SUVmax in the cranial arteries. Visual and semiquantitative assessments showed moderate agreement (Fleiss kappa 0.55). There was a positive correlation between the number of cranial symptoms and the SUVmax in the vertebral artery. Conclusion: FDG-PET/CT can reliably diagnose C-GCA by assessing cranial artery inflammation using SUVmax. Extending the use of FDG-PET/CT to include assessment of the cranial arteries may improve its diagnostic value in GCA and provide a suitable alternative to TAB. Moderate agreement between visual and semiquantitative assessment methods suggest diagnostic accuracy may be improved by further standardisation. (C) 2020 The Author(s). Published by Elsevier Inc.